langchain-hydradb

HydraDB integration for LangChain: give your chains and agents persistent, cross-session memory and retrieval powered by HydraDB.

Install

pip install langchain-hydradb   # once published; for local dev: pip install -e .

Prerequisites

• Python >= 3.9
• A HydraDB account: API key + tenant ID (hydradb.com)
• langchain-core >= 0.3

Quick start

from langchain_hydradb import HydraDBClient, HydraDBRetriever

client = HydraDBClient(api_key="sk_live_...", tenant_id="your-tenant")

# Use HydraDB as a retriever in any chain
retriever = HydraDBRetriever(client=client, kind="both", max_results=6)
docs = retriever.invoke("what did we decide about auth?")

# Write durable memory
client.add_text("We deploy on Fridays only.", infer=True)

As chat memory

from langchain_core.runnables.history import RunnableWithMessageHistory
from langchain_hydradb import HydraDBChatMessageHistory

chain_with_memory = RunnableWithMessageHistory(
    chain,
    lambda session_id: HydraDBChatMessageHistory(client, session_id),
    input_messages_key="input",
    history_messages_key="history",
)

What's included

Notes

• Public API only. Writes use the public knowledge path (app_knowledge via /context/ingest); the memory-family write route is not publicly exposed, so add_text/add_conversation store as knowledge. Recall kind may still be "memory", "knowledge", or "both" - default is "knowledge".
• Ingestion is asynchronous; recall a source only after it finishes indexing.
• The client depends only on requests; no HydraDB SDK required.

Test

pip install -e ".[test]"
pytest

License

Apache-2.0 - Copyright (c) 2026 HydraDB